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distilbert-base-uncased-finetuned-infovqa

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-infovqa
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilbert-base-uncased-finetuned-infovqa
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.8872
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 250500
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.02 | 100 | 4.7706 |
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+ | No log | 0.05 | 200 | 4.4399 |
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+ | No log | 0.07 | 300 | 3.8175 |
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+ | No log | 0.09 | 400 | 3.8306 |
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+ | 3.3071 | 0.12 | 500 | 3.6480 |
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+ | 3.3071 | 0.14 | 600 | 3.6451 |
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+ | 3.3071 | 0.16 | 700 | 3.4974 |
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+ | 3.3071 | 0.19 | 800 | 3.4686 |
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+ | 3.3071 | 0.21 | 900 | 3.4703 |
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+ | 3.5336 | 0.23 | 1000 | 3.3165 |
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+ | 3.5336 | 0.25 | 1100 | 3.3634 |
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+ | 3.5336 | 0.28 | 1200 | 3.3466 |
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+ | 3.5336 | 0.3 | 1300 | 3.3411 |
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+ | 3.5336 | 0.32 | 1400 | 3.2456 |
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+ | 3.3593 | 0.35 | 1500 | 3.3257 |
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+ | 3.3593 | 0.37 | 1600 | 3.2941 |
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+ | 3.3593 | 0.39 | 1700 | 3.2581 |
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+ | 3.3593 | 0.42 | 1800 | 3.1680 |
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+ | 3.3593 | 0.44 | 1900 | 3.2077 |
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+ | 3.2436 | 0.46 | 2000 | 3.2422 |
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+ | 3.2436 | 0.49 | 2100 | 3.2529 |
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+ | 3.2436 | 0.51 | 2200 | 3.2681 |
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+ | 3.2436 | 0.53 | 2300 | 3.1055 |
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+ | 3.2436 | 0.56 | 2400 | 3.0174 |
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+ | 3.093 | 0.58 | 2500 | 3.0608 |
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+ | 3.093 | 0.6 | 2600 | 3.0200 |
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+ | 3.093 | 0.63 | 2700 | 2.9884 |
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+ | 3.093 | 0.65 | 2800 | 3.0041 |
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+ | 3.093 | 0.67 | 2900 | 2.9700 |
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+ | 3.0087 | 0.69 | 3000 | 3.0993 |
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+ | 3.0087 | 0.72 | 3100 | 3.0499 |
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+ | 3.0087 | 0.74 | 3200 | 2.9317 |
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+ | 3.0087 | 0.76 | 3300 | 3.0817 |
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+ | 3.0087 | 0.79 | 3400 | 3.0035 |
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+ | 2.9694 | 0.81 | 3500 | 3.0850 |
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+ | 2.9694 | 0.83 | 3600 | 2.9948 |
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+ | 2.9694 | 0.86 | 3700 | 2.9874 |
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+ | 2.9694 | 0.88 | 3800 | 2.9202 |
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+ | 2.9694 | 0.9 | 3900 | 2.9322 |
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+ | 2.8277 | 0.93 | 4000 | 2.9195 |
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+ | 2.8277 | 0.95 | 4100 | 2.8638 |
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+ | 2.8277 | 0.97 | 4200 | 2.8809 |
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+ | 2.8277 | 1.0 | 4300 | 2.8872 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.3
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+ - Pytorch 1.9.0+cu111
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+ - Datasets 1.14.0
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+ - Tokenizers 0.10.3